I've been teaching Go for several years and I keep seeing the same picture: developers learn the syntax, write simple REST services, but when it comes to truly complex challenges—high loads, microservice architecture, distributed systems—problems arise. Usually, it's not a lack of language knowledge, but a systemic understanding of how to build reliable backends. This is exactly the problem that the course 'Go for Backend (gRPC)' on the asibiont.com platform solves.
Go has long become the #1 language for backend development in large companies. Google, Uber, Dropbox, Wildberries, and Avito write their services in it. Demand for Go developers is consistently high, and middle- and senior-level vacancies remain open for months. But simply knowing Go is not enough—you need to be able to design services that withstand thousands of requests per second, handle errors correctly, scale easily, and don't crash on restart. That's exactly what this course is about.
What is the 'Go for Backend (gRPC)' Course
This is a practical course for those who have already mastered the basics of Go and want to move to the next level. You don't just learn individual libraries—you assemble a complete production service with all the necessary elements: concurrent request handling, the efficient gRPC data exchange protocol, proper database work, tests, and monitoring.
The course is not for programming beginners. It is expected that you already know how to write Go: you know syntax, structs, interfaces, and basic work with goroutines. Everything else—from concurrency patterns to building distributed systems—you'll get here.
Main Course Topics
| Topic | What you'll master | Why it's needed |
|---|---|---|
| Concurrency in Go | goroutines, channels, worker pool patterns, fan-in/fan-out | To efficiently use multi-core processors and handle thousands of concurrent connections |
| gRPC | Protocol Buffers, server and client implementation, streaming | To build fast and type-safe microservice APIs instead of slow REST |
| HTTP middleware | Middleware layers: logging, authorization, rate limiting | To reuse cross-cutting logic and make code cleaner |
| Dependency injection | Containers and interfaces, manual DI | To test components independently and easily swap databases or external services |
| Working with databases | Connection pool, transactions, prepared SQL queries | To write stable code without connection leaks |
| Table-driven tests | Table-driven tests, mocks, coverage | To test different scenarios without duplicating code |
| Graceful shutdown | Proper shutdown with waiting for in-flight requests | To deploy new versions without losing user data |
| Monitoring | pprof, OpenTelemetry, tracing, metrics | To find and eliminate bottlenecks before users notice them |
What You'll Learn After Taking the Course
Imagine you've been tasked with building a service that receives data from hundreds of clients simultaneously. If you've only studied the basics of Go, you'd write a simple HTTP server using net/http that would start crashing under growing load. In this course, you'll learn how to:
- Design concurrent services — with worker pools, goroutine limiting, correct context and timeout handling. You'll be able to explain why mutexes aren't always the best choice and when to use channels.
- Use gRPC as an alternative to REST — gRPC runs over HTTP/2, transmits data in the binary Protocol Buffers format, automatically generates client code, and supports streaming requests. In real backends, this can provide several-fold performance gains compared to REST.
- Build a proper architecture — with dependency injection and interfaces, so you can easily swap components and write tests without hitting a real database.
- Write production code — with graceful shutdown, pprof metrics for CPU and memory profiling, and full observability through OpenTelemetry.
After the course, you'll be able to confidently pass interviews for Go backend developer positions or take on complex challenges in your current job. This isn't theory—all topics are practiced through hands-on assignments that mirror real production tasks.
Who This Course Is For
The course will be useful for:
- Backend developers using other languages (Java, Python, PHP) who want to switch to Go and immediately understand its strengths.
- Junior/beginner Go developers who have already built training projects and want to learn how real services are built in companies.
- Developers working with high-load systems who need tools for concurrent processing and monitoring.
- Team leads and architects who choose a stack for new services and want to make decisions based on best practices.
If you're planning to build a service that will serve millions of users, and performance and reliability matter to you—this course is for you.
How Learning Works on asibiont.com
Many of my students ask: why not just watch video lessons? The thing is, video is passive consumption. You watch someone write code, and you get the illusion of understanding. On the asibiont.com platform, learning is structured differently: you read text lectures and immediately complete practical assignments. This format forces you to work actively.
The platform uses its own proprietary technology—a neural network that generates personalized lessons for each student. This doesn't mean a chatbot replaces a live instructor. No. The neural network performs another, more important function: it builds an individual learning path.
How does it work? At the start of the course, you take an entry test, and the neural network determines your level. If you're confident with goroutines but have never used interfaces in a DI context, the program will automatically adjust the lesson order: first filling in the gaps, then moving to the new topic. If middleware is difficult for you, the neural network will provide additional examples, similar and simpler explanations, illustrated with real-world cases.
Every explanation adapts to your level: for a beginner, the neural network uses simple analogies; for an experienced developer, it goes straight to the subtleties and nuances. You get exactly the material you need, without fluff or repetition of what you already know.
Why AI Learning Is Modern and Effective
AI-based learning technologies are no longer science fiction. Assistants already help developers write code, and neural networks generate documentation. At asibiont.com, we've applied AI to pedagogy: the neural network doesn't just give everyone the same assignments—it adapts to each student.
Individual Pace and Level
In a typical group, weaker students fall behind and stronger ones get bored. AI adapts assignment difficulty in real time: if you quickly solve channel-related problems, the neural network makes the next lesson harder—adding nontrivial patterns that require nontrivial solutions. If you make mistakes, the system suggests additional exercises to practice exactly those topics.
Active Learning Instead of Passive Watching
Research in cognitive science shows that actively completing assignments is significantly more effective than watching videos or reading theory. Text lessons are supplemented with interactive examples that you must analyze, modify, and run. The neural network checks understanding and gives hints if you get stuck.
Plain-Language Explanations
Complex topics like gRPC or OpenTelemetry can be explained in dozens of different ways. The neural network is trained to choose wording adapted to your level. If you already know what TCP/IP is, it will build on that. If not, it will simplify the material until it becomes clear.
Saving Time
The average developer spends about 20–30 hours independently studying a new topic, sorting through articles from various sources, documentation, and YouTube tutorials. Here, the program is structured logically: from simple concepts to complex ones, with a clear sequence and practice. You save time by not jumping from topic to topic.
The Bottom Line
As an instructor, I see that developers who take this course come to interviews with a completely different level of confidence. They don't say 'I tried using gRPC'—they say 'I know when gRPC makes sense and how to design APIs.' That's a qualitative shift in mindset.
The course 'Go for Backend (gRPC)' is an opportunity to shorten your path from junior to solid middle and prepare for work in teams where Go is used for high-load services. All materials are available in text format, and you can study 24/7, at any convenient time, from anywhere—all you need is a browser.
Start learning today. Go to the course page: Go for Backend (gRPC). Explore the curriculum, try the first lesson—and perhaps this is where you'll find the knowledge you've been missing for your next career step.
See you on the course!
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